Mourad Gridach
- Artificial Intelligence top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition
- Information Systems
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Hatem HaddadHala Mulkiİsmail BabaoğluIrina VoiculescuRobail YasrabLior DrukkerJ. Alison NobleJianbo Jiao
- Topics
- Natural Language Processing Techniques (7 papers)Topic Modeling (6 papers)Sentiment Analysis and Opinion Mining (4 papers)
- Cited by
- Artificial IntelligenceComputer Vision and Pattern RecognitionManagement Science and Operations Research
- Partner nations
- MoroccoUnited KingdomTürkiye
In The Last Decade
Mourad Gridach
14 papers receiving 281 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 244
- Molecular Biology 85
- Computer Vision and Pattern Recognition 53
- Information Systems 30
- Radiology, Nuclear Medicine and Imaging 26
Countries citing papers authored by Mourad Gridach
This map shows the geographic impact of Mourad Gridach's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mourad Gridach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mourad Gridach more than expected).
Fields of papers citing papers by Mourad Gridach
This network shows the impact of papers produced by Mourad Gridach. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mourad Gridach. The network helps show where Mourad Gridach may publish in the future.
Co-authorship network of co-authors of Mourad Gridach
This figure shows the co-authorship network connecting the top 25 collaborators of Mourad Gridach. A scholar is included among the top collaborators of Mourad Gridach based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mourad Gridach. Mourad Gridach is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 43 | |
| 4 | 3 | |
| 5 | 17 | |
| 6 | 2 | |
| 7 | OXENDONET: A Dilated Convolutional Neural Networks For Endoscopic Artefact Segmentation. | 5 |
| 8 | 17 | |
| 9 | 7 | |
| 10 | 147 | |
| 11 | 16 | |
| 12 | 16 | |
| 13 | Character-Aware Neural Networks for Arabic Named Entity Recognition for Social Media | 24 |
| 14 | Developing a New System for Arabic Morphological Analysis and Generation | 5 |
| 15 | Design and Realization of an Arabic Morphological Automaton: New Approach for Arabic Morphological Analysis and Generation | 0 |
| 16 | 3 |
About Mourad Gridach
Mourad Gridach is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Language and Linguistics, having authored 16 papers that have together received 306 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (7 papers), Topic Modeling (6 papers) and Sentiment Analysis and Opinion Mining (4 papers). The work is most often cited by research in Artificial Intelligence (244 citations), Computer Vision and Pattern Recognition (53 citations) and Management Science and Operations Research (19 citations). Mourad Gridach has collaborated with scholars based in Morocco, United Kingdom and Türkiye. Frequent co-authors include Hatem Haddad, Hala Mulki, İsmail Babaoğlu, Irina Voiculescu, Robail Yasrab, Lior Drukker, J. Alison Noble, Jianbo Jiao and Aris T. Papageorghiou. Their work appears in journals such as Neurocomputing, Neural Networks and Applied Soft Computing.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.